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Published on: November 21, 2013
Subtypes of Clinical High Risk for Psychosis that Predict Antipsychotic Effectiveness in Long-Term Remission
TianHong Zhang1, JunJie Wang2, LiHua Xu1
1Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai.
Introduction:
In a previous report, we used canonical correlation analysis to classify individuals with clinical high risk (CHR) of psychosis into the 3 subtypes: subtype-1, characterized by extensive negative symptoms and cognitive deficits, appeared to have the highest risk for conversion to psychosis; subtype-2, characterized by thought and behavioral disorganization, with moderate cognitive impairment; subtype-3, characterized by the mildest symptoms and cognitive deficits. The present study attempted to identify these subtypes' response to antipsychotic (AP) treatment.
Methods:
A total of 289 individuals with CHR were identified and followed up for 2 years. Individuals with CHR were classified by subtype. Use of APs was examined at 2-month, 1-year, and 2-year follow-up interviews that inquired after the subjects' medication history since the first visit. The main outcome was remission, determined according to global assessment of function (GAF) score (i. e., functional outcome) and SIPS positive symptom score (symptomatic outcome) at the follow-up points.
Results:
Among the 289 individuals with CHR included in the current analysis, 223 (77.2%) were treated using APs for at least 2 weeks during the follow-up period. Individuals with CHR tended to show significant improvement in both symptoms and function after 2 years, but subtypes exhibited significantly different trajectories. Subtype status can predict AP treatment outcome in terms of remission. The likelihood of remission differed significantly among the subtype groups. The remission rates for individuals with subtypes 1-3 treated using AP were 13.5%, 36.1%, and 67.0%, respectively.
Discussion:
These subtypes may be of clinical value in AP treatment decision-making in the CHR population.
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